Diploma in Artificial Intelligence & Machine Learning

Fee: ₹60,000.00

Dr. Priti Maheshwary | Professor FSA

Curriculum

Paper 1 - Introduction to Artificial Intelligence & Machine Learning
- Chapter 1 - Introduction to Artificial Intelligence Page
- Chapter 2 - Introduction to machine Learning Page
- Chapter 3 - Introduction to Deep Learning Page
- Chapter 4 - Real World Applications of AI/ML Page
- Chapter 5 - Ethics in Machine Learning Page
- Chapter 6 - Evaluation of Machine Learning codes

Paper 2 - Mathematics and Statistics for AI/ML
- Chapter 1 - Python Statistics Libraries Page
- Chapter 2 - Vectors Page
- Chapter 3 - Matrix Page
- Chapter 4 - Probability and Statistics Page
- Chapter 5 - Descriptive Statistics
- Chapter 6 - Random Numbers

Paper 3 - Python Programming & Data Manipulation and Visualization
- Chapter 1 - Introduction to Python View
- Chapter 3 - Conditions/Loops Page
- Chapter 4 - Libraries in Python Page
- Chapter 5 - Numpy
- Chapter 6 - Panda Page
- Chapter 7 - Data Story Telling Page
- Chapter 8 - Data Acquisition Page
- Chapter 9 - Data Cleaning and Preprocessing Page
- Chapter 10 - Data Manipulation Using Excel Page
- Chapter 11 - Data Manipulation using MySQL
- Chapter 12 - Advance Queries
- Chapter 13 - Data Visualization Using Python Page
- Chapter 14 - Data Visualization Using PowerBI Page

Module 4 - Supervised & Unsupervised learning
- Chapter 1 - Introduction to Supervised Learning Page
- Chapter 2 - Linear Regression View
- Chapter 3 - Multiple Linear Regression Page
- Chapter 4 - Logistic Regression Page
- Chapter 5 - SVM Page
- Chapter 6 - KNN Page
- Chapter 7 - Random Forest Algorithm Page
- Chapter 8 - Naïve Bayes Page
- Chapter 9 - Types of Learning Page
- Chapter 10 - Clustering in Machine Learning Page
- Chapter 11 - K means Clustering Page
- Chapter 12 - Elbow Method for optimal value of k in Kmeans Page
- Chapter 13 - Mean-shift Clustering Page
- Chapter 14 - Fuzzy Clustering Page

Module 5 - Reinforcement Learning and Story Telling
- Chapter 1 - Introduction Reinforcement Learning
- Chapter 2 - Q-Learning Algorithms
- Chapter 3 - Introduction to Thompson Sampling
- Chapter 4 - Genetic Algorithm for Reinforcement Learning
- Chapter 5 - SARSA Reinforcement
- Chapter 6 - Q-Learning in Python Example
- Chapter 7 - Story Telling

Module 6 - Tensor Flow PyTouch
- Chapter 1 - Tensor Flow Basic
- Chapter 2 - Tensor Flow Perceptron

Instructor

Dr. Priti Maheshwary

Professor FSA

IT, Computer Science

Presently working in Future Skill Academy. Involved in Computer Science and Engineering for over 20 years in higher education and training. Her career has included various software development projects, teaching, research and administrative roles. She enjoys teaching and looking into how to improve student learning experience. Published around 50 research papers in refereed journals and conferences, 7 book chapters, 6 Patents. 8 PhD thesis completed under her guidance in the field of Internet of Things, Smart Cities, Ubiquitous Computing, Wireless Sensor Network, VANET, Image Processing specialized in Satellite Images, AI/ML & Deep Learning, and Cyber Security. Also done more than 10 projects in the field of Research and Consultancy.

4,9 1045 1100 Learners

Dr. Pooja Bijlani

Trainer (Subject Expert ) Future Skill Academy

AI ML , Data science , Full Stack Web Development , Full Stack Java Development

Presently she is working as a IT Trainer (Subject Expert )at Future Skill Academy, AISECT,Bhopal. She is having over 15 years of academic and research experience. Expert in Programming Languages C,C++,Python , Java ,React SpringBoot ,Artificial Intelligence , Machine Learning and Data Science. Students accolades her programming language teaching skills . Having experience in number of End to End projects in Natural language Processing , Computer Vision and Python Desktop Application GUI. Web Designing.

4.9 968 1087 Learners

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